chatlearn/tools/check_parameter_sync.py (35 lines of code) (raw):
# Copyright 2024 Alibaba Group Holding Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Check ParameterSync"""
import argparse
import os
import torch
def chatlearn_compare(expected_dir, actural_dir):
total = 0
diff = 0
not_exists = 0
for tp_rank in os.listdir(actural_dir):
for param in os.listdir(os.path.join(actural_dir, tp_rank)):
actual_fname = os.path.join(actural_dir, tp_rank, param)
expected_fname = os.path.join(expected_dir, tp_rank, param)
message = f"{tp_rank}|{param}"
total += 1
if not os.path.exists(expected_fname):
print(f"NOT_EXISTS|{message}|NOT_EXISTS", flush=True)
not_exists += 1
continue
ta = torch.load(actual_fname, map_location="cpu")
tb = torch.load(expected_fname, map_location="cpu")
if not torch.allclose(ta, tb):
print(f"DIFF|{message}|{ta.shape}|{ta.mean()}|{tb.shape}|{tb.mean()}", flush=True)
else:
print(f"PASS|{message}")
print(f"ALL: {all}, DIFF: {diff}, NOT_EXISTS: {not_exists}")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--root_dir",
type=str,
required=True,
help="Root dir to check the dumped parameters")
args = parser.parse_args()
dir1 = os.path.join(args.root_dir, "before_sync_paramter")
dir2 = os.path.join(args.root_dir, "after_sync_paramter")
chatlearn_compare(dir1, dir2)